---
language: en
license: mit
task_categories:
- text-classification
tags:
- decision-timing
- control-geometry
- reasoning
- clarus
- sios
size_categories:
- n<1K
pretty_name: Decision Timing Classification v0.1
---

# What this dataset does

This dataset tests whether a model can judge whether action is being taken at the right time.

# Core stability idea

Good decisions depend on timing.

The same action can be stabilizing early and useless late.

Decision timing is appropriate when action occurs before buffers close, damage spreads, or recovery options disappear.

# Prediction target

Binary label:

- 1 = decision timing is appropriate
- 0 = decision timing is too late or poorly timed

# Row structure

Each row contains:

- scenario_id
- scenario_text
- claim
- label

# Files

- data/train.csv
- data/test.csv
- scorer.py
- README.md

# Evaluation

```bash
python scorer.py --predictions predictions.csv --truth data/test.csv

Structural Note

This dataset is intentionally small.

Its purpose is to test whether a model can detect timing-sensitive control windows.

License

MIT